blending image

Author: ahmedliem

blending.py

@@ -0,0 +1,70 @@
+import cv2 as cv
+import numpy as np
+import glob
+import os
+import logging
+from multiprocessing import Process
+
+if not os.path.exists('logs'):
+	os.mkdir('logs')
+
+logging.basicConfig(filename='logs/blending.txt',
+                            filemode='a',
+                            format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
+                            datefmt='%H:%M:%S',
+                            level=logging.DEBUG)
+
+
+def blending(images: str, background: str, alphas: list):
+	"""
+
+	"""
+	image_paths = glob.glob(images + '/*.jpg')
+	background_paths = glob.glob(background + '/*.jpg')
+	for background_path in background_paths:
+		for idx, image_path in enumerate(image_paths):
+			# try:
+			# imread image
+			print(image_path)
+			img = cv.imread(image_path)
+			# x, y, _ = img.shape
+			# img_cropped = img[10: y-10, 10: x+10]
+			# cv.imwrite('test.jpg', img_cropped)
+			# get shape to resize background
+			shape = img.shape[1], img.shape[0]
+			# imread and resize backround
+			backround_name = background_path.split('/')[-1]
+			bgr_name = backround_name.split('.')[0]
+			img_bgr = cv.imread(background_path)
+			bgr_resized = cv.resize(img_bgr, shape)
+			# setup save path
+			image_name = image_path.split('/')[-1]
+			print(image_name)
+			name = image_name.split('.')[0]
+			print(name)
+			saver = 'output_red'
+			if not os.path.exists(saver):
+				os.makedirs(saver)
+			# add blending with alpha
+			for alpha in np.asarray(alphas):
+			    dst = cv.addWeighted(img, alpha, bgr_resized, 1-alpha, 0)
+			    img_path = saver + '/{}_{}_{}_{}.jpg'.format(bgr_name, name, idx, alpha)
+			    cv.imwrite(img_path, dst)
+			# except Exception as e:
+			# 	logging.error("log blending image", exc_info=True)
+			# 	continue
+
+if __name__ == '__main__':
+	
+	images = 'red_images'
+	background = 'background'
+	alpha = [ 0.5, 0.8]
+	processes = []
+	for i in range(14):
+		p = Process(target=blending, args=(images, background, alpha))
+		p.daemon = True
+		p.start()
+		processes.append(p)
+
+	for p in processes:
+		p.join()

change_color_text.py

@@ -0,0 +1,67 @@
+import cv2
+import numpy as np
+import tqdm
+import glob
+import os
+import time
+import logging
+from multiprocessing import Process
+
+
+logging.basicConfig(filename='logs/change_color.txt',
+                            filemode='a',
+                            format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
+                            datefmt='%H:%M:%S',
+                            level=logging.DEBUG)
+
+def change_color(images, target_1, target_2, threshold, output='color_changed'):
+	"""
+		Check color of each pixel
+		if mean of all color value of each pixel bigger than threshold:
+			color value assign for tartget_1 color
+		else:
+			color value assign for target_2 color
+	"""
+	if os.path.exists(output):
+		os.makedirs(output)
+	counter = []
+	paths = glob.glob(images + '/*.jpg')
+	for path in tqdm.tqdm(paths):
+		start = time.time()
+		try:
+			img = cv2.imread(path)
+			for i in range(img.shape[1]):
+			    for j in range(img.shape[0]):
+			        channels_xy = img[j,i]
+			        if np.mean(channels_xy) > threshold:    
+			            img[j,i] = target_1
+			        else:
+			            img[j,i] = target_2
+			saver = os.path.join(output, path.split('/')[-1])
+			cv2.imwrite(saver, img)
+		except Exception as e:
+			logging.error("log exception change color text", exc_info=True)
+			continue
+		counter.append(time.time() - start)
+	print("Total time: {} and average time: {}".format(sum(counter), sum(counter)/len(counter)))
+
+
+if __name__ == '__main__':
+
+	images = 'test'
+	red = [0, 0, 255] # BGR
+	white = [255, 255, 255] 
+	threshold = 120
+	num_thread = 16
+	change_color(images, white, red, threshold)
+	# processes = []
+
+	# for i in range(num_thread):
+	# 	p = Process(target=change_color, args=(images, white, red, threshold))
+	# 	p.daemon = True
+	# 	p.start()
+	# 	processes.append(p)
+
+	# for p in processes:
+	# 	p.join()
+

crop.py

@@ -0,0 +1,10 @@
+import cv2
+import glob
+import tqdm
+
+for path in tqdm.tqdm(glob.glob('output/*.jpg')):
+	name = path.split('/')[-1]
+	img = cv2.imread(path)
+	h, w, _ = img.shape
+	cropped = img[420:h-500, 400:w-400]
+	cv2.imwrite('cropped/black/{}'.format(name), cropped)

pdf2img.py

@@ -0,0 +1,65 @@
+from pdf2image import convert_from_path
+import os
+import random
+import tqdm
+import logging
+import PIL
+from multiprocessing import Process
+
+# logging defineable
+logging.basicConfig(filename='logs.txt',
+                    filemode='a',
+                    format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
+                    datefmt='%H:%M:%S',
+                    level=logging.DEBUG)
+def convert():
+	path_pdf = './red_pdf'
+	path_img = './red_images'
+	if not os.path.exists(path_img):
+		os.mkdir(path_img)
+
+	# PIL.Image.MAX_IMAGE_PIXELS = 933120000
+	# Image.MAX_IMAGE_PIXELS
+
+	pdfs = os.listdir(path_pdf)
+	for idx, pdf in enumerate(tqdm.tqdm(pdfs)):
+		try:
+			file = os.path.join(path_pdf, pdf)
+			name = pdf.split('.')[0]
+			# output_filename = os.path.join(path_img, name)
+			# #
+			# if not os.path.exists(output_filename):
+			# 	os.mkdir(output_filename)
+			#
+			# print("file: ", output_filename)
+			PIL.Image.MAX_IMAGE_PIXELS = None
+			pages = convert_from_path(file, 500)
+			# print("pages: ", pages)
+			for idx_page, page in enumerate(pages):
+				page.save(path_img+'/{}_{}.jpg'.format(idx, idx_page), 'JPEG')
+		except Exception as e:
+			logging.error("Logging load data", exc_info=True)
+			continue
+
+def re_convert():
+	data = 'images_1'
+	for file in tqdm.tqdm(os.listdir(data)):
+		try:
+			path_file = os.path.join(data, file)
+			if len(os.listdir(path_file)) == 0:
+				pdf = file + '.pdf'
+				print(path_file)
+				PIL.Image.MAX_IMAGE_PIXELS = None
+				pages = convert_from_path('pdf/' + pdf, 300)
+				# print("pages: ", pages)
+				for idx_page, page in enumerate(pages):
+					page.save(path_file+'/{}_{}.jpg'.format(file, idx_page), 'JPEG')
+		except Exception as e:
+			logging.error("Logging load data", exc_info=True)
+			continue
+
+if __name__ == '__main__':
+    convert()
+
+
+